---
title: "Analysis On Footballers"
output: 
  flexdashboard::flex_dashboard:
    orientation: columns
    vertical_layout: fill
    source_code: embed
    theme: cerulean
---

```{r setup, include=FALSE}
library(flexdashboard)
library(dplyr)
library(ggplot2)
library(DT)
sonuc <- read.csv("result.csv")
sonuc_ <-distinct(sonuc, cleaned_names, .keep_all = TRUE)
sonuc_
library(dplyr)
yeni <- sonuc_ %>% 
  select(cleaned_names  , Age, cleaned_teams,Height,Weight,foot ,Best.overall,Best.position, Growth,Value,Wage,Release.clause) %>% 
    rename(Names = cleaned_names, Teams = cleaned_teams, Foot = foot)

yeni$age_group  <- cut(yeni$Age, breaks = c(0,18, 25, 30, 40, max(yeni$Age)), labels = c("Under 18", "Young", "Middle-aged", "Old", "Very Old"))

```

# Start

Column {data-width=250 .tabset}
-----------------------------------------------------------------------

### Scatter Plot

```{r}
# bu bir grafik 
ggplot(yeni, aes(x = Best.overall, y = Value)) +
  geom_point(aes(color = Value, size = Value), alpha = 0.5) +  # Noktaları mavi renkte ve boyut 3 yapma
  scale_color_gradient(low = "blue", high = "red", name = "Value")+
  labs(title = "Potential vs Value Scatter Plot", x = "Potential", y = "Value") +  # Başlık ve eksen etiketleri ekleme
  theme_minimal()



```

### Interactive Pie Plot

```{r}
library(plotly)
library(dplyr)
pozisyon_frekans <- table(yeni$Best.position)

# Veri çerçevesi oluşturma
df <- data.frame(
  pozisyon = names(pozisyon_frekans),
  frekans = as.numeric(pozisyon_frekans)
)

# Pasta grafiği oluşturma
plot_ly(
  data = df,
  labels = ~pozisyon,
  values = ~frekans,
  type = "pie"
) %>%
  layout(
    title = "Distribution of Positions Played by Footballers",
    showlegend = TRUE,
    legend = list(title = list(text = 'Positions')),
    marker = list(
      colors = c("#FF3333", "#FF9933", "#FFCC66", "#99FF66", "#66CCCC", "#3399FF", "#9966FF", "#FF66B2", "#FF6699", "#FF3333", "#FF9933", "#FFCC66", "#99FF66", "#66CCCC", "#3399FF", "#9966FF", "#FF66B2")
    )
  )
# Futbolcuların poziyonlarına göre oluşturulan pasta grafiği

```

Column {data-width=250}
-----------------------------------------------------------------------

### Histogram Plot

```{r fig.width = 12, fig.height= 5}
  
ggplot(sonuc, aes(x = Best.overall)) +
  geom_histogram(binwidth = 0.99, fill = "skyblue", color = "black") +
  labs(title = "Distribution Of Overall Ratings Achieved By Footballers", x = "Best Potential", y = "Frequency") +
  theme(
    plot.background = element_rect(fill = "transparent", color = NA),
    panel.background = element_rect(fill = "transparent", color = NA)
  ) +
  theme(
    plot.title = element_text(size = 20),  
    axis.title.x = element_text(size = 16),  
    axis.title.y = element_text(size = 16),  
    axis.text.x = element_text(size = 14),  
    axis.text.y = element_text(size = 14),  
    legend.title = element_text(size = 16), 
    legend.text = element_text(size = 14)  
  )
  
#Distribution Of Overall Ratings Achieved By Footballers
```

### Bar Plot

```{r fig.width = 12, fig.height= 5}
library(plotly)
bar<-ggplot(yeni, aes(x = age_group, fill = age_group)) +
  geom_bar() +
  theme_minimal() +
  labs(title = "Bar Plot of Player Ages by Age Group",
       x = "Age Group",
       y = "Count",
       fill = "Age Group") +
  scale_fill_manual(values = c("#FF6F61", "#6B5B95", "#88B04B", "#F7CAC9", "#92A8D1"))+
   theme(
    plot.title = element_text(size = 20),  
    axis.title.x = element_text(size = 16),  
    axis.title.y = element_text(size = 16),  
    axis.text.x = element_text(size = 14),  
    axis.text.y = element_text(size = 14),  
    legend.title = element_text(size = 16), 
    legend.text = element_text(size = 14)  
  )
bar
```

# Info Data


Row {data-height=450}
-------------------------------------
### Dataset 
```{r}
library(DT)
datatable(yeni, options = list(
  pageLength = 10,
  editable = 'cell'
  
))
```



Row {data-height=350}
-------------------------------------
### List of the variable names
```{r}

#variables <- data.frame("Variable Names" = names(yeni))
#datatable(variables, options = list(dom = 't'))

library(DT)

variables <- data.frame("Variable Names" = names(yeni))

datatable(variables, options = list(dom = 't')) %>%
  formatStyle(columns = names(variables), fontSize = '10px')

```

### Main summary of the data
```{r fig.width = 5, fig.height= 5}
library(kableExtra)
summary_data <- summary(yeni)

de_stat<-yeni %>%
  select(-Names,-Teams,-Foot,-Best.position,-age_group)%>% 
  summary() %>%
  knitr::kable() %>% 
  kable_styling(font_size = 10)
de_stat
#datatable(summary_data)
```

# About me

### Panel including these information
```{r}
library(DT)
library(tibble)

# Verileri oluşturma ve değişken isimlerini İngilizce yapma
veri <- tibble(
  Name = "Kamil Göçer",
  Number = 666,
  Date = as.Date("2024-06-09"),
  Dataset_Name = "players_3120.csv"
)

library(DT)
library(tibble)
library(gt)

# Verileri oluşturma ve değişken isimlerini İngilizce yapma
veri <- tibble(
  Name = "Kamil Göçer",
  Number = 666,
  Date = as.Date("2024-06-09"),
  Dataset_Name = "players_3120.csv"
)

veri %>% 
  gt() %>% 
  tab_header(
    title = "Bilgilerim"
    
  ) 
```